An iterated eigenvalue algorithm for approximating roots of univariate polynomials

  • Authors:
  • Steven Fortune

  • Affiliations:
  • Bell Laboratories, Murray Hill, NJ

  • Venue:
  • Journal of Symbolic Computation - Computer algebra: Selected papers from ISSAC 2001
  • Year:
  • 2002

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Abstract

We discuss an iterative algorithm that approximates all roots of a univariate polynomial. The iteration is based on floating-point computation of the eigenvalues of a generalized companion matrix. With some assumptions, we show that the algorithm approximates the roots within about logρ/εχ(P) iterations, where ∈ is the relative error of floating-point arithmetic, ρ is the relative separation of the roots, and χ(P) is the condition number of the polynomial. Each iteration requires an n × n floating-point eigenvalue computation, n the polynomial degree, and evaluation of the polynomial to floating-point accuracy at up to n points.We describe a careful implementation of the algorithm, including many techniques that contribute to the practical efficiency of the algorithm. On some hard examples of ill-conditioned polynomials, e.g. high-degree Wilkinson polynomials, the implementation is an order of magnitude faster than the Bini-Fiorentino implementation mpsolve.